553 hw3
Ellie Kissin
HW3 Data set 12; life expectancy and income
loading in needed libraries:
loading in needed data:
Reshape ‘Income Per Person’ to make a longitudinal dataset such that the resulting dataset has three columns: country, year, and income
reshape pop total
Reshape ‘Life Expectancy in Years’ such that the resulting dataset has columns country, year, and life expectancy
Merge the two datsets above into a new one called LifeExpIncom that has the following variables: country, year, lifeExp, and income
Merge LifeExpIncom with country region so that the final dataset has info about income, life expectancy, and country region.
Make an interactive scatter plot to display the association between life expectancy and income for the year 2015. - point size to be proportional to the population size – might need to rescale for it to look appropriate - different colors for different countries - Include the country name and population size in the hover text
#filter to the year 2015
LEIP_f_15 <- LEIP_f%>%filter(year==2015)
LEIP_f_15## country income life expectancy pop_num region
## 1 Afghanistan 1750 57.9 33700000 Asia
## 2 Albania 11000 77.6 2920000 Europe
## 3 Algeria 13700 77.3 39900000 Africa
## 4 Andorra 46600 82.5 78000 Europe
## 5 Angola 6230 64.0 27900000 Africa
## 6 Antigua and Barbuda 20100 77.2 99900 Americas
## 7 Argentina 19100 76.5 43400000 Americas
## 8 Armenia 8180 75.4 2920000 Asia
## 9 Australia 43800 82.6 23800000 Oceania
## 10 Austria 44100 81.4 8680000 Europe
## 11 Azerbaijan 16700 71.8 9620000 Asia
## 12 Bahamas 21700 73.6 387000 Americas
## 13 Bahrain 44500 76.8 1370000 Asia
## 14 Bangladesh 3130 72.4 161000000 Asia
## 15 Barbados 15400 76.6 284000 Americas
## 16 Belarus 17200 73.3 9490000 Europe
## 17 Belgium 41700 80.9 11300000 Europe
## 18 Belize 8060 71.9 359000 Americas
## 19 Benin 1990 63.9 10600000 Africa
## 20 Bhutan 7740 73.8 787000 Asia
## 21 Bosnia and Herzegovina 10900 77.4 3540000 Europe
## 22 Botswana 15400 64.6 2210000 Africa
## 23 Brazil 14700 75.2 206000000 Americas
## 24 Bulgaria 17000 75.0 7180000 Europe
## 25 Burkina Faso 1550 60.3 18100000 Africa
## 26 Burundi 749 60.0 10200000 Africa
## 27 Cambodia 3290 68.3 15500000 Asia
## 28 Cameroon 2990 59.7 22800000 Africa
## 29 Canada 43000 81.7 35900000 Americas
## 30 Central African Republic 626 49.7 4550000 Africa
## 31 Chad 2050 59.2 14000000 Africa
## 32 Chile 22500 80.1 17800000 Americas
## 33 China 13600 76.3 1400000000 Asia
## 34 Colombia 13000 78.0 48200000 Americas
## 35 Comoros 1410 67.3 777000 Africa
## 36 Congo, Dem. Rep. 750 60.9 76200000 Africa
## 37 Costa Rica 14900 80.9 4810000 Americas
## 38 Cote d'Ivoire 3250 59.2 23100000 Africa
## 39 Croatia 20600 77.3 4240000 Europe
## 40 Cuba 20000 78.9 11500000 Americas
## 41 Cyprus 30400 80.5 1160000 Asia
## 42 Czech Republic 30400 78.9 10600000 Europe
## 43 Denmark 45500 80.7 5690000 Europe
## 44 Djibouti 3140 66.1 927000 Africa
## 45 Dominica 10100 71.7 73200 Americas
## 46 Dominican Republic 13400 75.5 10500000 Americas
## 47 Ecuador 10800 77.9 16100000 Americas
## 48 Egypt 10100 71.9 93800000 Africa
## 49 El Salvador 7850 75.0 6310000 Americas
## 50 Equatorial Guinea 27200 65.2 1180000 Africa
## 51 Eritrea 1240 63.4 4850000 Africa
## 52 Estonia 27300 77.2 1320000 Europe
## 53 Ethiopia 1530 65.2 99900000 Africa
## 54 Fiji 8760 65.5 892000 Oceania
## 55 Finland 39000 81.5 5480000 Europe
## 56 France 37800 82.2 64500000 Europe
## 57 Gabon 16800 66.0 1930000 Africa
## 58 Gambia 1590 67.0 1980000 Africa
## 59 Georgia 9030 73.7 3950000 Asia
## 60 Germany 43800 80.8 81700000 Europe
## 61 Ghana 3930 65.4 27600000 Africa
## 62 Greece 24100 81.0 11200000 Europe
## 63 Grenada 12700 71.4 107000 Americas
## 64 Guatemala 7290 72.5 16300000 Americas
## 65 Guinea 1180 60.0 12100000 Africa
## 66 Guinea-Bissau 1420 58.2 1770000 Africa
## 67 Guyana 7060 67.0 769000 Americas
## 68 Haiti 1650 63.9 10700000 Americas
## 69 Honduras 4310 72.5 8960000 Americas
## 70 Hungary 24800 75.7 9780000 Europe
## 71 Iceland 42700 82.2 330000 Europe
## 72 India 5750 68.2 1310000000 Asia
## 73 Indonesia 10400 71.4 258000000 Asia
## 74 Iraq 14900 67.6 36100000 Asia
## 75 Ireland 60900 81.1 4700000 Europe
## 76 Israel 32000 82.0 8060000 Asia
## 77 Italy 34200 82.3 59500000 Europe
## 78 Jamaica 8110 74.9 2870000 Americas
## 79 Japan 37800 83.8 128000000 Asia
## 80 Jordan 8490 76.8 9160000 Asia
## 81 Kenya 2840 66.3 47200000 Africa
## 82 Kiribati 1870 61.6 112000 Oceania
## 83 Kuwait 69300 79.8 3940000 Asia
## 84 Kyrgyz Republic 3240 71.1 5870000 Asia
## 85 Latvia 23100 74.8 1990000 Europe
## 86 Lebanon 13100 80.1 5850000 Asia
## 87 Lesotho 2780 49.6 2170000 Africa
## 88 Liberia 785 63.8 4500000 Africa
## 89 Libya 13500 74.2 6230000 Africa
## 90 Lithuania 27000 74.9 2930000 Europe
## 91 Luxembourg 95300 82.0 567000 Europe
## 92 Madagascar 1380 62.3 24200000 Africa
## 93 Malawi 1090 59.4 17600000 Africa
## 94 Malaysia 25000 75.4 30700000 Asia
## 95 Maldives 12000 79.3 418000 Asia
## 96 Mali 1920 61.4 17500000 Africa
## 97 Malta 34400 81.3 428000 Europe
## 98 Marshall Islands 3670 64.7 53000 Oceania
## 99 Mauritania 3600 70.0 4180000 Africa
## 100 Mauritius 18900 74.5 1260000 Africa
## 101 Mexico 16700 76.2 126000000 Americas
## 102 Mongolia 11400 68.2 2980000 Asia
## 103 Montenegro 15300 76.9 628000 Europe
## 104 Morocco 7290 74.8 34800000 Africa
## 105 Mozambique 1120 59.0 28000000 Africa
## 106 Myanmar 5070 69.5 52400000 Asia
## 107 Namibia 9910 64.3 2430000 Africa
## 108 Nepal 2300 69.7 28700000 Asia
## 109 Netherlands 46400 81.6 16900000 Europe
## 110 New Zealand 34600 81.5 4610000 Oceania
## 111 Nicaragua 4960 78.0 6080000 Americas
## 112 Niger 897 61.2 19900000 Africa
## 113 Nigeria 5670 64.0 181000000 Africa
## 114 North Korea 1390 70.6 25200000 Asia
## 115 Norway 63700 82.1 5200000 Europe
## 116 Oman 40100 77.4 4200000 Asia
## 117 Pakistan 4700 67.3 189000000 Asia
## 118 Palestine 2650 71.8 4660000 Asia
## 119 Panama 20700 78.7 3970000 Americas
## 120 Papua New Guinea 2750 60.5 7920000 Oceania
## 121 Paraguay 8640 74.4 6640000 Americas
## 122 Peru 11800 79.5 31400000 Americas
## 123 Philippines 6880 70.1 102000000 Asia
## 124 Poland 25300 77.7 38300000 Europe
## 125 Portugal 26500 80.8 10400000 Europe
## 126 Qatar 120000 80.5 2480000 Asia
## 127 Romania 20500 75.1 19900000 Europe
## 128 Russia 24100 70.8 144000000 Europe
## 129 Rwanda 1720 67.3 11600000 Africa
## 130 Samoa 5560 71.7 194000 Oceania
## 131 Sao Tome and Principe 2940 70.3 196000 Africa
## 132 Saudi Arabia 50700 76.8 31600000 Asia
## 133 Senegal 2300 65.9 15000000 Africa
## 134 Serbia 13300 75.7 8850000 Europe
## 135 Seychelles 25500 73.7 93700 Africa
## 136 Sierra Leone 1320 57.6 7240000 Africa
## 137 Singapore 80900 83.6 5540000 Asia
## 138 Slovak Republic 28300 76.8 5440000 Europe
## 139 Slovenia 29100 80.7 2070000 Europe
## 140 Solomon Islands 2050 62.8 587000 Oceania
## 141 Somalia 623 57.3 13900000 Africa
## 142 South Africa 12400 61.8 55300000 Africa
## 143 South Korea 34200 80.9 50600000 Asia
## 144 South Sudan 1810 58.9 11900000 Africa
## 145 Spain 32200 82.9 46400000 Europe
## 146 Sri Lanka 11100 77.2 20700000 Asia
## 147 St. Lucia 10700 76.1 177000 Americas
## 148 St. Vincent and the Grenadines 10500 71.6 109000 Americas
## 149 Sudan 4290 68.0 38600000 Africa
## 150 Suriname 14800 71.2 553000 Americas
## 151 Sweden 45500 82.1 9760000 Europe
## 152 Switzerland 56500 83.1 8320000 Europe
## 153 Syria 3500 68.4 18700000 Asia
## 154 Tajikistan 2640 71.6 8550000 Asia
## 155 Tanzania 2490 63.5 53900000 Africa
## 156 Thailand 15200 77.6 68700000 Asia
## 157 Timor-Leste 2150 72.6 1240000 Asia
## 158 Togo 1350 62.1 7420000 Africa
## 159 Tonga 5190 70.3 106000 Oceania
## 160 Trinidad and Tobago 31300 73.1 1360000 Americas
## 161 Tunisia 10800 77.4 11300000 Africa
## 162 Turkey 23400 79.0 78300000 Asia
## 163 Uganda 1690 61.6 40100000 Africa
## 164 Ukraine 7470 71.9 44700000 Europe
## 165 United Arab Emirates 66000 76.5 9150000 Asia
## 166 United Kingdom 38500 80.8 65400000 Europe
## 167 United States 52800 78.8 320000000 Americas
## 168 Uruguay 19800 77.1 3430000 Americas
## 169 Uzbekistan 5700 70.0 31000000 Asia
## 170 Vanuatu 2810 63.6 265000 Oceania
## 171 Venezuela 15600 75.5 31200000 Americas
## 172 Yemen 2640 67.2 26900000 Asia
## 173 Zambia 3630 58.1 16100000 Africa
## 174 Zimbabwe 1890 58.3 15800000 Africa
## sub.region year
## 1 Southern Asia 2015
## 2 Southern Europe 2015
## 3 Northern Africa 2015
## 4 Southern Europe 2015
## 5 Sub-Saharan Africa 2015
## 6 Latin America and the Caribbean 2015
## 7 Latin America and the Caribbean 2015
## 8 Western Asia 2015
## 9 Australia and New Zealand 2015
## 10 Western Europe 2015
## 11 Western Asia 2015
## 12 Latin America and the Caribbean 2015
## 13 Western Asia 2015
## 14 Southern Asia 2015
## 15 Latin America and the Caribbean 2015
## 16 Eastern Europe 2015
## 17 Western Europe 2015
## 18 Latin America and the Caribbean 2015
## 19 Sub-Saharan Africa 2015
## 20 Southern Asia 2015
## 21 Southern Europe 2015
## 22 Sub-Saharan Africa 2015
## 23 Latin America and the Caribbean 2015
## 24 Eastern Europe 2015
## 25 Sub-Saharan Africa 2015
## 26 Sub-Saharan Africa 2015
## 27 South-eastern Asia 2015
## 28 Sub-Saharan Africa 2015
## 29 Northern America 2015
## 30 Sub-Saharan Africa 2015
## 31 Sub-Saharan Africa 2015
## 32 Latin America and the Caribbean 2015
## 33 Eastern Asia 2015
## 34 Latin America and the Caribbean 2015
## 35 Sub-Saharan Africa 2015
## 36 Sub-Saharan Africa 2015
## 37 Latin America and the Caribbean 2015
## 38 Sub-Saharan Africa 2015
## 39 Southern Europe 2015
## 40 Latin America and the Caribbean 2015
## 41 Western Asia 2015
## 42 Eastern Europe 2015
## 43 Northern Europe 2015
## 44 Sub-Saharan Africa 2015
## 45 Latin America and the Caribbean 2015
## 46 Latin America and the Caribbean 2015
## 47 Latin America and the Caribbean 2015
## 48 Northern Africa 2015
## 49 Latin America and the Caribbean 2015
## 50 Sub-Saharan Africa 2015
## 51 Sub-Saharan Africa 2015
## 52 Northern Europe 2015
## 53 Sub-Saharan Africa 2015
## 54 Melanesia 2015
## 55 Northern Europe 2015
## 56 Western Europe 2015
## 57 Sub-Saharan Africa 2015
## 58 Sub-Saharan Africa 2015
## 59 Western Asia 2015
## 60 Western Europe 2015
## 61 Sub-Saharan Africa 2015
## 62 Southern Europe 2015
## 63 Latin America and the Caribbean 2015
## 64 Latin America and the Caribbean 2015
## 65 Sub-Saharan Africa 2015
## 66 Sub-Saharan Africa 2015
## 67 Latin America and the Caribbean 2015
## 68 Latin America and the Caribbean 2015
## 69 Latin America and the Caribbean 2015
## 70 Eastern Europe 2015
## 71 Northern Europe 2015
## 72 Southern Asia 2015
## 73 South-eastern Asia 2015
## 74 Western Asia 2015
## 75 Northern Europe 2015
## 76 Western Asia 2015
## 77 Southern Europe 2015
## 78 Latin America and the Caribbean 2015
## 79 Eastern Asia 2015
## 80 Western Asia 2015
## 81 Sub-Saharan Africa 2015
## 82 Micronesia 2015
## 83 Western Asia 2015
## 84 Central Asia 2015
## 85 Northern Europe 2015
## 86 Western Asia 2015
## 87 Sub-Saharan Africa 2015
## 88 Sub-Saharan Africa 2015
## 89 Northern Africa 2015
## 90 Northern Europe 2015
## 91 Western Europe 2015
## 92 Sub-Saharan Africa 2015
## 93 Sub-Saharan Africa 2015
## 94 South-eastern Asia 2015
## 95 Southern Asia 2015
## 96 Sub-Saharan Africa 2015
## 97 Southern Europe 2015
## 98 Micronesia 2015
## 99 Sub-Saharan Africa 2015
## 100 Sub-Saharan Africa 2015
## 101 Latin America and the Caribbean 2015
## 102 Eastern Asia 2015
## 103 Southern Europe 2015
## 104 Northern Africa 2015
## 105 Sub-Saharan Africa 2015
## 106 South-eastern Asia 2015
## 107 Sub-Saharan Africa 2015
## 108 Southern Asia 2015
## 109 Western Europe 2015
## 110 Australia and New Zealand 2015
## 111 Latin America and the Caribbean 2015
## 112 Sub-Saharan Africa 2015
## 113 Sub-Saharan Africa 2015
## 114 Eastern Asia 2015
## 115 Northern Europe 2015
## 116 Western Asia 2015
## 117 Southern Asia 2015
## 118 Western Asia 2015
## 119 Latin America and the Caribbean 2015
## 120 Melanesia 2015
## 121 Latin America and the Caribbean 2015
## 122 Latin America and the Caribbean 2015
## 123 South-eastern Asia 2015
## 124 Eastern Europe 2015
## 125 Southern Europe 2015
## 126 Western Asia 2015
## 127 Eastern Europe 2015
## 128 Eastern Europe 2015
## 129 Sub-Saharan Africa 2015
## 130 Polynesia 2015
## 131 Sub-Saharan Africa 2015
## 132 Western Asia 2015
## 133 Sub-Saharan Africa 2015
## 134 Southern Europe 2015
## 135 Sub-Saharan Africa 2015
## 136 Sub-Saharan Africa 2015
## 137 South-eastern Asia 2015
## 138 Eastern Europe 2015
## 139 Southern Europe 2015
## 140 Melanesia 2015
## 141 Sub-Saharan Africa 2015
## 142 Sub-Saharan Africa 2015
## 143 Eastern Asia 2015
## 144 Sub-Saharan Africa 2015
## 145 Southern Europe 2015
## 146 Southern Asia 2015
## 147 Latin America and the Caribbean 2015
## 148 Latin America and the Caribbean 2015
## 149 Northern Africa 2015
## 150 Latin America and the Caribbean 2015
## 151 Northern Europe 2015
## 152 Western Europe 2015
## 153 Western Asia 2015
## 154 Central Asia 2015
## 155 Sub-Saharan Africa 2015
## 156 South-eastern Asia 2015
## 157 South-eastern Asia 2015
## 158 Sub-Saharan Africa 2015
## 159 Polynesia 2015
## 160 Latin America and the Caribbean 2015
## 161 Northern Africa 2015
## 162 Western Asia 2015
## 163 Sub-Saharan Africa 2015
## 164 Eastern Europe 2015
## 165 Western Asia 2015
## 166 Northern Europe 2015
## 167 Northern America 2015
## 168 Latin America and the Caribbean 2015
## 169 Central Asia 2015
## 170 Melanesia 2015
## 171 Latin America and the Caribbean 2015
## 172 Western Asia 2015
## 173 Sub-Saharan Africa 2015
## 174 Sub-Saharan Africa 2015#making a ggplot
plot_LEIP <- ggplot(LEIP_f_15, aes(income, `life expectancy`))+geom_point(aes(color=country, size=pop_num))+ labs(x = "Income",y = "Life Expectancy", title = "Association between Income and Life Expectancy")
#lot_LEIP
ggplotly(plot_LEIP)Make an animated scatter plot that shows pattern of change in the relationship between life expectancy and income over the years. - Set the point size to be proportional to the population size - Use different colors for different regions. - can use a subset of years – I don’t have to use all the years available
plot_LEIP_99 <- ggplot(LEIP_f_99_18, aes(income, `life expectancy`))+geom_point(aes(color=region, size=pop_num), alpha=0.3)+ labs(title = 'Year: {frame_time}', x = "Income",y = "Life Expectancy")+transition_time(year)+ease_aes('linear')
animate(plot_LEIP_99)## Warning: Removed 3 rows containing missing values (geom_point).
## Removed 3 rows containing missing values (geom_point).
## Removed 3 rows containing missing values (geom_point).
## Removed 3 rows containing missing values (geom_point).
## Removed 3 rows containing missing values (geom_point).
## Removed 3 rows containing missing values (geom_point).
## Removed 3 rows containing missing values (geom_point).
## Removed 3 rows containing missing values (geom_point).
## Removed 3 rows containing missing values (geom_point).
## Removed 3 rows containing missing values (geom_point).
anim_save('plot_LEIP_99.gif')